Development of Functional Magnetic Resonance Imaging (fMRI) Database

• Main Authors: Kao Wei-Lun, 高偉倫
• Other Authors: 陳志宏
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/01865951883623240726

碩士 === 國立臺灣大學 === 電機工程學研究所 === 89 === The functional Magnetic Resonance Imaging, (fMRI) is a non-invasive tool for analyzing human brain functions, and it is often used for diagnosis and research of the human brain. In recent years, fMRI has been applied to medicine and cognitive science neuropsychology in order to discover the secrets of the human brain. Actually, fMRI has become one of the most powerful tools for the analysis of the human brain functions. The fMRI data are in 3D spatial plus 1D temporal formats, and therefore it needs sizable disk spaces to be stored. Consequently a difficulty in data storage, data retrieving and experimental data comparison arises. In addition, we have to record the attributes and physiological data of all subjects; hence we have the need to establish an integrated system, whose function is to incorporate different types of data as well as to facilitate the statistical analysis and comparison of the fMRI experimental results. So far, we have accomplished a database architecture, which successfully integrates fMRI image data and text mode data, and provides a practical mechanism of data searching and group comparison. Users can choose their desired searching criteria through an user interface, circle arbitrary 3D spatial areas and find out all matched image data. While inspecting the querying results, users can also click the mouse at any area to look up its anatomical and physiological functions. Regarding the aspect of implementation, we utilize our system to analyze the experiments of coldness stimulation conducted by Dr. Wu, Ming-Ting at Kaohsiung Veterans General Hospital, and have found plenty of correlations between different experiments. Concerning the capability of system expansion, present design of our database system enables future integration of respiratory, EEG and blood pressure signals through plug-ins, which effectively increases system flexibility. Thus our system suffices the need of an remarkable examining and statistical tool for the investigative work of cerebral functional imaging.